肺癌合并脓毒症mHLA-DR、CD39<sup>+</sup>Treg及IL-10表达与预后相关性分析

doi:10.3877/cma.j.issn.1674-6902.2023.02.004

目的

分析肺癌合并脓毒症患者中外周单核细胞HLA-DR、外周血CD39⁺ Tregs水平和IL-10表达水平对病情及预后评估的价值。

方法

选择2020年9月至2021年12月我院收治的肺癌合并脓毒症的患者68例，根据其严重程度分为脓毒症组38例，脓毒性休克组30例；同期36例未合并脓毒症的肺癌患者为对照组；测定各组患者入院后外周单核细胞HLA-DR、外周血CD39⁺ Treg及IL-10的水平，分析三种指标与严重程度的相关性，采用ROC曲线分析三种指标及联合检测对脓毒症严重程度和预后评估的能力。

结果

①脓毒症组血清中的CD39⁺ Treg比例、IL-10水平均显著高于对照组(3.92±1.35 vs. 2.14±0.86%)、(37.08±5.32 vs. 9.22±1.75)pg/ml(P<0.01)，mHLA-DR水平在感染前7 d均低于脓毒性休克组和对照组，P<0.01；在入院第7天脓毒症组中HLA-DR降至最低，与入院时水平差异有显著性(91.07±1.14 vs. 84.59±0.7%，P<0.01)；②68例脓毒症肺癌患者中，死亡22例；与生存者相比，死亡者ΔHLA-DR7水平明显降低，CD39⁺ Treg比例、IL-10水平明显升高，P<0.01；③脓毒症组中多因素Logistic回归分析显示ΔHLA-DR7(OR＝2.195，P<0.001)、CD39⁺ Treg(OR＝2.853，P＝0.015)、IL-10(OR＝1.868，P＝0.002)与APACHEⅡ及SOFA评分是脓毒症预后不良的危险因素；④ΔHLA-DR7评价脓毒症预后的曲线下面积为0.911，截断值为8.7%时，敏感度为89.28%，特异度为97.6%，大于CD39⁺ Treg和IL-10，P<0.01；三种指标联合的预后评估能力(曲线下面积为0.925，敏感度为96.61%，特异度为94.32%)明显高于三者的单一检测或两两联合检测。

结论

ΔHLA-DR7是肺癌伴脓毒症严重程度和预后评估的一个良好指标，ΔHLA-DR7与CD39⁺ Treg和IL-10三者联合能够显著提高脓毒症的诊断和预后评估的水平。

关键词: mHLA-DR, CD39⁺ Tregs, 白细胞介素-10, 支气管肺癌, 脓毒症

Objective

To study the value of peripheral monocyte HLA-DR, peripheral blood CD39⁺ Tregs and IL-10 expression in evaluating the state and prognosis of patients with lung cancer complicated with sepsis.

Methods

A total of 68 patients with lung cancer complicated by sepsis who were hospitalized in our hospital from September 2020 to December 2021 were selected and divided into sepsis divided into sepsis group 38 cases, septic shock group 30 cases, lung cancer without sepsis group 36 cases. The levels of mHLA-DR, CD39⁺ Treg and IL-10 in peripheral monocytes were measured after admission. The correlation between the three indexes and the severity was analyzed. ROC curve was used to analyze the three indexes and the ability of combined detection to evaluate the severity and prognosis of sepsis.

Results

① The proportion of CD39⁺ Treg and IL-10 level in lung cancer patients with sepsis were significantly higher than those in non-sepsis group (3.92±1.35 vs. 2.14±0.86%), (37.08±5.32 vs. 9.22±1.75 pg/ml) (P<0.01). The mHLA-DR level was lower than that in non-sepsis group and control group 7 days before infection (P<0.01). HLA-DR decreased to the lowest level in sepsis group on the 7 th day after admission, which was significantly different from that at admission (91.07±1.14 vs. 84.59±0.7%) (P<0.01). The proportion of CD39⁺ Treg and IL-10 levels were higher than those in the survival group (P<0.01); ③Multivariate logistic regression analysis in the lung cancer sepsis group showed that ΔHLA-DR7 (OR=2.195, P<0.001), CD39⁺ Treg (OR=2.853, P=0.015), IL-10 (OR=1.868, P=0.002) and APACHE Ⅱ and SOFA scores were independent risk factors for poor prognosis of sepsis; ④ The area under the curve of ΔHLA-DR7 in evaluating the prognosis of sepsis was 0.911, and when the cutoff value was 8.7%, the sensitivity was 89.28% and the specificity was 97.6%) was greater than that of CD39⁺ Treg and IL-10, and the difference was statistically significant (P<0.01).

Conclusion

ΔHLA-DR 7 is a good index for evaluating the severity and prognosis of lung cancer with sepsis. ΔHLA-DR7 combined with CD39⁺ Treg and IL-10 can significantly improve the diagnosis and prognosis of sepsis.

Key words: mHLA-DR, CD39⁺ Tregs, Interleukin-10, Bronchogenic carcinoma, Sepsis

表1 患者mHLA-DR、CD39⁺ Tregs和IL-10指标比较(±s)

组　别	入院时mHLA-DR	入院第3天mHLA-DR	入院第7天mHLA-DR	mHLA-DR3(%)(第3天-第0日差值)	mHLA-DR7(%)(第7天-第0日差值)	CD39⁺ Tregs(%)	IL-10(pg/ml)
脓毒症组	91.07±1.14^a	87.07±1.22^a	84.59±0.75^ac	4.78±0.61	7.53±1.22^a	3.92±1.35^a	37.08±5.32^a
脓毒症休克组	88.09±1.02^a	84.53±0.98^a	76.24±0.61^ac	6.12±0.49	9.87±1.39^a	5.33±1.81^a	58.76±7.29^ab
对照组	95.07±0.86	94.38±0.99	96.14±1.22	0.96±0.05	0.83±0.08	2.14±0.86	9.22±1.75

表1 患者mHLA-DR、CD39⁺ Tregs和IL-10指标比较(±s)

组　别	入院时mHLA-DR	入院第3天mHLA-DR	入院第7天mHLA-DR	mHLA-DR3(%)(第3天-第0日差值)	mHLA-DR7(%)(第7天-第0日差值)	CD39⁺ Tregs(%)	IL-10(pg/ml)
脓毒症组	91.07±1.14^a	87.07±1.22^a	84.59±0.75^ac	4.78±0.61	7.53±1.22^a	3.92±1.35^a	37.08±5.32^a
脓毒症休克组	88.09±1.02^a	84.53±0.98^a	76.24±0.61^ac	6.12±0.49	9.87±1.39^a	5.33±1.81^a	58.76±7.29^ab
对照组	95.07±0.86	94.38±0.99	96.14±1.22	0.96±0.05	0.83±0.08	2.14±0.86	9.22±1.75

表2 肺癌合并脓毒血症生存者与死亡者指标比较(±s)

临床资料	生存者(n＝46)	死亡者(n＝22)	统计量	P值
年龄(岁)	58.2±6.4	63.9±7.5	2.658	0.266
性别(男/女，n)	21/25	16/6	4.401^c	0.412
脓毒症分级(n)			4.319^a	0.000
脓毒症	30	8
脓毒症休克	8	12
第7天HLA-DR(%)	86.72±0.59	75.69±0.64	17.410	0.010
ΔHLA-DR3(%)	5.89±0.53	6.51±0.40	2.856	0.171
ΔHLA-DR7(%)	7.86±0.47	9.07±0.32	12.115	0.000
CD39⁺ Treg(%)	4.16±1.19	6.08±2.15^b	1.112	0.000
IL-10(pg/ml)	31.39±4.78	62.15±8.34^a	7.319	0.000
APACHEⅡ评分(分)	19.02±4.11	28.56±6.91^b	8.356	0.000
SOFA评分(分)	3.42±1.75	6.63±5.86^a	5.024	0.000

表2 肺癌合并脓毒血症生存者与死亡者指标比较(±s)

临床资料	生存者(n＝46)	死亡者(n＝22)	统计量	P值
年龄(岁)	58.2±6.4	63.9±7.5	2.658	0.266
性别(男/女，n)	21/25	16/6	4.401^c	0.412
脓毒症分级(n)			4.319^a	0.000
脓毒症	30	8
脓毒症休克	8	12
第7天HLA-DR(%)	86.72±0.59	75.69±0.64	17.410	0.010
ΔHLA-DR3(%)	5.89±0.53	6.51±0.40	2.856	0.171
ΔHLA-DR7(%)	7.86±0.47	9.07±0.32	12.115	0.000
CD39⁺ Treg(%)	4.16±1.19	6.08±2.15^b	1.112	0.000
IL-10(pg/ml)	31.39±4.78	62.15±8.34^a	7.319	0.000
APACHEⅡ评分(分)	19.02±4.11	28.56±6.91^b	8.356	0.000
SOFA评分(分)	3.42±1.75	6.63±5.86^a	5.024	0.000

表3 各项指标二元Logistic回归单因素分析

临床资料	估计值	标准误	Wald值	OR值(95%CI)	P值
年龄	0.009	0.012	0.512	1.723(0.549~2.897)	0.012
性别	0.678	0.329	3.162	2.949(0.915~4.982)	0.182
HLA-DR (第0天)	－2.276	1.942	1.374	0.103(0.002~4.616)	0.241
HLA-DR (第3天)	－3.404	2.692	1.599	0.033(0.000~6.502)	0.206
HLA-DR (第7天)	－0.452	1.801	0.063	0.953(0.046~1.859)	0.086
ΔHLA-DR3	1.877	2.261	0.689	0.153(0.02~12.867)	0.406
ΔHLA-DR7	1.658	0.001	14.247	0.169(0.054~0.283)	0.001
CD39⁺ Tregs	0.217	0.045	2.336	1.240(0.941~1.634)	0.006
IL-10	0.164	0.034	3.391	1.068(0.973~1.166)	0.017
APACHEⅡ	0.218	0.042	8.870	2.860(1.693~4.027)	0.000
SOFA	0.674	0.168	15.114	2.008(0.765~3.941)	0.000

表3 各项指标二元Logistic回归单因素分析

临床资料	估计值	标准误	Wald值	OR值(95%CI)	P值
年龄	0.009	0.012	0.512	1.723(0.549~2.897)	0.012
性别	0.678	0.329	3.162	2.949(0.915~4.982)	0.182
HLA-DR (第0天)	－2.276	1.942	1.374	0.103(0.002~4.616)	0.241
HLA-DR (第3天)	－3.404	2.692	1.599	0.033(0.000~6.502)	0.206
HLA-DR (第7天)	－0.452	1.801	0.063	0.953(0.046~1.859)	0.086
ΔHLA-DR3	1.877	2.261	0.689	0.153(0.02~12.867)	0.406
ΔHLA-DR7	1.658	0.001	14.247	0.169(0.054~0.283)	0.001
CD39⁺ Tregs	0.217	0.045	2.336	1.240(0.941~1.634)	0.006
IL-10	0.164	0.034	3.391	1.068(0.973~1.166)	0.017
APACHEⅡ	0.218	0.042	8.870	2.860(1.693~4.027)	0.000
SOFA	0.674	0.168	15.114	2.008(0.765~3.941)	0.000

表4 肺癌伴脓毒症死亡的多因素Logistic回归分析

变　量	估计值	标准误	Wald值	OR值	OR值的95%CI	P值
年龄	0.112	0.326	3.452	1.779	1.082~2.475	0.000
ΔHLA-DR7	0.035	0.010	9.812	2.195	1.046~3.344	0.000
CD39⁺ Treg	1.374	0.028	2.966	2.853	0.959~3.812	0.015
IL-10	0.169	0.201	5.605	1.868	0.917~2.819	0.002
APACHEⅡ	0.152	0.476	7.273	2.379	1.421~3.338	0.000
SOFA	0.063	0.012	8.119	2.163	1.205~3.121	0.000

表4 肺癌伴脓毒症死亡的多因素Logistic回归分析

变　量	估计值	标准误	Wald值	OR值	OR值的95%CI	P值
年龄	0.112	0.326	3.452	1.779	1.082~2.475	0.000
ΔHLA-DR7	0.035	0.010	9.812	2.195	1.046~3.344	0.000
CD39⁺ Treg	1.374	0.028	2.966	2.853	0.959~3.812	0.015
IL-10	0.169	0.201	5.605	1.868	0.917~2.819	0.002
APACHEⅡ	0.152	0.476	7.273	2.379	1.421~3.338	0.000
SOFA	0.063	0.012	8.119	2.163	1.205~3.121	0.000

表5 肺癌合并脓毒症预后评估ROC曲线

指　标	AUC(95%CI)	临界值	敏感度(%)	特异度(%)	约登指数
ΔHLA-DR7(%)	0.911(0.874~0.923)	8.7%	89.28	86.05	0.75
IL-10(pg/ml)	0.816(0.712~0.926)	32.7%	78.62	60.19	0.39
CD39⁺ Treg(%)	0.832(0.755~0.912)	3.6%	80.34	74.72	0.55
mHLA-DR+CD39+Treg	0.918(0.876~0.984)	－	94.15	91.47	0.86
mHLA-DR+IL-10	0.893(0.843~0.957)	－	92.87	90.28	0.83
CD39⁺ Treg+IL-10	0.874(0.827~0.953)	－	91.55	88.69	0.80
mHLA-DR+CD39⁺Treg+IL-10	0.925(0.899~0.996)	－	96.61	94.32	0.91

表5 肺癌合并脓毒症预后评估ROC曲线

指　标	AUC(95%CI)	临界值	敏感度(%)	特异度(%)	约登指数
ΔHLA-DR7(%)	0.911(0.874~0.923)	8.7%	89.28	86.05	0.75
IL-10(pg/ml)	0.816(0.712~0.926)	32.7%	78.62	60.19	0.39
CD39⁺ Treg(%)	0.832(0.755~0.912)	3.6%	80.34	74.72	0.55
mHLA-DR+CD39+Treg	0.918(0.876~0.984)	－	94.15	91.47	0.86
mHLA-DR+IL-10	0.893(0.843~0.957)	－	92.87	90.28	0.83
CD39⁺ Treg+IL-10	0.874(0.827~0.953)	－	91.55	88.69	0.80
mHLA-DR+CD39⁺Treg+IL-10	0.925(0.899~0.996)	－	96.61	94.32	0.91

1	Taccone FS, Artigas AA, Sprung CL, et al. Characteristics and outcomes of cancer patients in European ICUs[J]. Crit Care, 2009, 13(1): R15.
2	Vandijck DM, Benoit DD, Depuydt PO, et al. Impact of recent intravenous chemotherapy on outcome in severe sepsis and septic patients with cancer and sepsis 307 shock patients with hematological malignancies[J]. Intensive Care Med, 2008, 34(5): 847-855.
3	Hampshire PA, Welch CA, McCrossan LA, et al. Admission factors associated with hospital mortality in patients with haematological malignancy admitted to UK adult, general critical care units: a secondary analysis of the ICNARC Case Mix Programme Database[J]. Crit Care, 2009, 13(4): R137.
4	Tolsma V, Schwebel C, Azoulay E, et al. Sepsis severe or septic shock: outcome according to immune status and immunodeficiency profile[J]. Chest, 2014, 146(5): 1205-1213.
5	Yin J, Chen Y, Huang JL, et al. Prognosis-related classification and dynamic monitoring of immune status in patients with sepsis: A prospective observational study[J]．World J Emerg Med, 2021, 12(3): 185-191.
6	Vuk-Pavlovic S. Rebuilding immunity in cancer patients[J]. Blood Cells Mol Dis, 2008, 40(1): 94-100.
7	Zanza C, Caputo G, Tornatore G, et al. Cellular immuno-profile in septic human host: A scoping review[J]. Biology (Basel), 2022, 11(11): 1626.
8	Mirouse A, Vigneron C, Llitjos JF, et al. Sepsis and cancer: An interplay of friends and foes[J]. Am J Respir Crit Care Med, 2020, 202(12): 1625-1635.
9	Peters van Ton AM, Kox M, Abdo WF, et al. Precision immunotherapy for sepsis[J]. Front Immunol, 2018, 9: 1926.
10	Fumeaux T, Pugin J. Is the measurement of monocytes HLA-DR expression useful in patient with sepsis[J]. Intensive Care Med, 2006, 32(8): 1106-1108.
11	Zhuang YG, Peng H, Chen YZ, et al. Dynamic monitoring of monocyte HLA-DR expression for the diagnosis, prognosis, and prediction of sepsis[J]. Front Biosci (Landmark Ed), 2017, 22(8): 1344-1354.
12	Tschaikowsky K, Hedwig-Geissing M, Schiele A, et al. Coincidence of pro- and anti-inflammatory responses in the early phase of severe sepsis: Longitudinal study of mononuclear histocompatibility leukocyte antigen-DR expression, procalcitonin, C-reactive protein, and changes in T-cell subsets in septic and postoperative patients[J]. Crit Care Med, 2002, 30(5): 1015-1023.
13	Le Tulzo Y, Pangault C, Amiot L, et al. Monocyte human leukocyte antigen-DR transcriptional downregulation by cortisol during septic shock[J]. Am J Respir Crit Care Med, 2004, 169(10): 1144-1151.
14	Pangault C, Le Tulzo Y, Tattevin P, et al. Down-modulation of granulocyte macrophage-colony stimulating factor receptor on monocytes during human septic shock[J]. Rit Care Med, 2006, 34(4): 1193-1201.
15	Winkler MS, Rissiek A, Priefler M, et al. Human leucocyte antigen (HLA-DR) gene expression is reducedin sepsis and correlates with impaired TNF-αresponse: A diagnostic tool for immunosuppression？[J]. PLoS One, 2017, 12(8): e0182427.
16	Becker C, Kubach J, Wijdenes J, et al. CD4-mediated functional activation of human CD4+CD25+ regulatory T cells[J]. Eur J Immunol, 2007, 37(5): 1217-1223.
17	Wachstein J, Tischer S, Figueiredo C, et al. HSP70 enhances immunosuppressive function of CD4(+)CD25(+)FoxP3(+) T regulatory cells and cytotoxicity in CD4(+)CD25(-) T cells[J]. PLoS One, 2012, 7(12): e51747.
18	Wang L, Xie Y, Zhu LJ, et al. An association between immunosenescence and CD4(+)CD25(+) regulatory T cells: a systematic review[J]. Biomed Environ Sci, 2010, 23(4): 327-232.
19	Tiemessen MM, Jagger AL, Evans HG, et al. CD4+CD25+Foxp3+ regulatory T cells induce alternative activation of human monocytes/macrophages[J]. Proc Natl Acad Sci U S A, 2007, 104(49): 19446-19451.
20	Borsellino G, Kleinewietfeld M, DiMitri D, et al. Expression of ectonucleotidase CD39 by Foxp3+Treg cells: hydrolysis of extracellular ATP and immune suppression[J]. Blood, 2007, 110(4): 1225-1232.
21	Liu J, Shi K, Chen M, et al. Elevated miR-155 expression induces immunosuppression via CD39(+) regulatory T-cells in sepsis patient[J]. Int J Infect Dis, 2015, 40: 135-141.
22	Huang H, Xu R, Lin F, et al. Highcirculating CD39(+) regulatory T cells predict poorsurvival for sepsis patients[J]. Int J Infect Dis, 2015, 30: 57-63.
23	Dimitrov E, Enchev E, Minkov G, et al. Outcome could be predicted by lower monocyte human leukocyte antigen-DR expression in patients with complicated intra-abdominal infections: A review. [J]. Surg Infect, 2020, 21(2): 77-80.
24	Mokart D, Textoris J, Chow-Chine L, et al. HLA-DR and B7-2 (CD86) monocyte expressions after major cancer surgery: profile in sepsis[J]. Minerva Anestesiol, 2011, 77(5): 522-527.
25	Li L, Chen L, Lin F, et al. Study of the expression of inflammatory factors IL-4, IL-6, IL-10, and IL-17 in liver failure complicated by coagulation dysfunction and sepsis[J]. J Inflamm Res, 2021, 14: 1447-1453.
26	Gogos CA, Drosou E, Bassaris HP, et al. Pro- versus anti-inflammatory cytokine profile in patients with severe sepsis: a marker for prognosis and future therapeutic options[J]. J Infect Dis, 2000, 181(1): 176-180.
27	Zhang W, Wang W, Hou W, et al. The diagnostic utility of IL-10, IL-17, and PCT in patients with sepsis infection[J]. Front Public Health, 2022, 10: 923457.
28	Hynninen M, Pettil V, Takkunen O, et al. Predictive value of monocyte histocompatibility leukocyte antigen-DR expression and plasma interleukin-4 and -10 levels in critically ill patients with sepsis[J]. Shock, 2003, 20(1): 1-4.
29	Wang S, Li T, Li Y, et al. Predictive value of four different scoring systems for septic patient′s outcome: a retrospective analysis with 311 patients[J]. Zhonghua Wei Zhong Bing Ji Jiu Yi Xue, 2017, 29(2): 133-138.
30	Nathan N, Sculier JP, Ameye L, et al. Sepsis and septic shock definitions in patients with cancer admitted in ICU[J]. J Intensive Care Med, 2021, 36(3): 255-261.

[1]	杨瑾, 刘雪克, 张媛媛, 金钧, 韦瑶. 肠道微生物来源石胆酸对脓毒症相关肝损伤的保护作用[J]. 中华危重症医学杂志(电子版), 2024, 17(04): 265-274.
[2]	张霞, 张瑞, 郑志波, 张勤. 紫草素调控乳酸化修饰和线粒体功能改善脓毒症心肌病小鼠的预后[J]. 中华危重症医学杂志(电子版), 2024, 17(04): 275-284.
[3]	张婧琦, 江洋, 孙佳璐, 唐兴喆, 赵宇飞, 崔颖, 李信响, 戴景月, 傅琳, 彭新桂. 基于肾周CT特征结合血清肌酐水平探讨脓毒症伴急性肾损伤的早期识别[J]. 中华危重症医学杂志(电子版), 2024, 17(04): 285-292.
[4]	李振翮, 魏长青, 甄国栋, 李振富. 脓毒症并发急性呼吸窘迫综合征患者血清S1P、Wnt5a变化及其临床意义[J]. 中华危重症医学杂志(电子版), 2024, 17(04): 293-300.
[5]	樊恒, 孙敏, 朱建华. 红景天苷通过抑制PI3K/AKT/mTOR信号通路对大鼠脓毒症急性肾损伤的保护作用[J]. 中华危重症医学杂志(电子版), 2024, 17(03): 188-195.
[6]	张璇, 高杨, 房雅君, 姚艳玲. 保护性机械通气在肺癌胸腔镜肺段切除术中的临床应用[J]. 中华肺部疾病杂志(电子版), 2024, 17(04): 563-567.
[7]	陶银花, 张红杰, 王亚岚, 陈莲, 张珺. 间歇式气压治疗预防肺癌化疗下肢深静脉血栓的临床分析[J]. 中华肺部疾病杂志(电子版), 2024, 17(04): 605-608.
[8]	任甜甜, 张玉慧, 祁玲霞, 朱梅冬, 胡佳. 多学科疼痛管理对胸腔镜肺叶切除术后胸痛及应激反应的影响分析[J]. 中华肺部疾病杂志(电子版), 2024, 17(04): 630-633.
[9]	林建琴, 孔令敏, 陆银凤, 陈勇, 金凤, 叶磊, 陈方梅. PERMA模式对肺癌患者治疗获益感及生活质量的影响分析[J]. 中华肺部疾病杂志(电子版), 2024, 17(04): 634-638.
[10]	殷国青, 曾莉, 贺斌峰, 孙芬芬. Rab26负性调控Nrf2增强肺癌耐药细胞对奥希替尼的敏感性[J]. 中华肺部疾病杂志(电子版), 2024, 17(03): 349-355.
[11]	邓世君, 刘晓青, 刘权兴. 信息化管理在肺癌围手术期中的临床应用[J]. 中华肺部疾病杂志(电子版), 2024, 17(03): 466-468.
[12]	胡梓菡, 彭菲, 孙骎, 杨毅. 细胞外囊泡在脓毒症血管内皮损伤作用中的研究进展[J]. 中华重症医学电子杂志, 2024, 10(03): 265-270.
[13]	刘娟丽, 马四清, 乌仁塔娜. 髓源性抑制细胞在脓毒症中的研究进展[J]. 中华重症医学电子杂志, 2024, 10(03): 271-278.
[14]	苏生林, 马金兰, 于弘明, 杨晓军. 单细胞测序技术在脓毒症免疫研究中的应用进展[J]. 中华重症医学电子杂志, 2024, 10(03): 279-286.
[15]	陈惠英, 邱敏珊, 邵汉权. 脓毒症诱发肠黏膜屏障功能损伤的风险因素模型构建与应用效果[J]. 中华消化病与影像杂志(电子版), 2024, 14(05): 448-452.

阅读次数

全文

摘要

选择文件类型/文献管理软件名称

选择包含的内容

Expression of mHLA-DR, CD39⁺ Treg and IL-10 in lung cancer patients with sepsis was correlated with the severity and prognosis of the disease

模态框（Modal）标题

选择文件类型/文献管理软件名称

选择包含的内容

Expression of mHLA-DR, CD39+ Treg and IL-10 in lung cancer patients with sepsis was correlated with the severity and prognosis of the disease

Expression of mHLA-DR, CD39⁺ Treg and IL-10 in lung cancer patients with sepsis was correlated with the severity and prognosis of the disease