结核病患者中靶向调控维生素D受体的microRNA的初步筛选

doi:10.3877/cma.j.issn.1674-6902.2020.06.003

目的

筛选与结核病相关，且靶向调控维生素D受体(vitamin D receptor, VDR)的microRNA(miRNA)，为深入研究维生素D(vitamin D, VitD)辅助抗结核病机制及其临床应用提供一定的参考依据。

方法

选择5例明确诊断肺结核病患者和5例非结核病的志愿者作为研究组和对照组。分别收集临床基线资料以及采集两组外周血单个核细胞(peripheral blood mononuclear cell, PBMC)作为临床样本，提取总RNA后，采用高通量测序技术(high-throughput sequencing)，检测两组间的miRNA差异表达情况。

结果

5例肺结核病患者和5例非结核病志愿者临床基线资料经统计学分析得出两组间23项指标的同质性和异质性，其中性别、年龄、吸烟饮酒习惯等两组间无统计学差异；体重指数(BMI)、总胆固醇(TC)、血红蛋白(Hb)白蛋白(ALB)、球蛋白(GLB)及总蛋白(TP)研究组低于对照组，有统计学差异(P<0.05)。高通量测序从研究组和对照组5对样本中共筛选出1 560条miRNAs，得到miRNA在两组中差异表达谱。分层聚类和火山图进一步综合分析发现研究组中最有差异的23条miRNAs(P<0.05)，其中15条miRNAs在研究组中表达下(∣LOG2FC∣>1)，8条miRNAs表达上调(FC>1)。综合高通量测序结果和生物信息学预测，从差异表达谱中筛选出2条有统计学意义且靶向VDR的miRNAs：hsa-miR-326(P<0.05、FC＝1.37)、hsa-miR-654-5p(P<0.05、∣LOG2FC∣＝1.06)。

结论

通过临床样本高通量测序分析及生物信息学预测，发现了结核病中的既差异表达又靶向VDR的两条miRNAs，这两条miRNAs可能是肺结核病潜在的诊断标志及新的治疗靶点，为结核病的防治提供了新的策略和方向。

关键词: 肺结核病, microRNA, 维生素D, 高通量测序, 生物信息学

Objective

MicroRNA with significantly differential expression and targeted regulation of Vitamin D receptor(VDR) in Tuberculosis were screened by High-throughput sequencing and bioinformatics methods, whichprovided the further study of Vitamin D anti-tuberculosis mechanism and clinical application.

Method

According to the inclusion and exclusion criteria, 5 patients with definite diagnosis of tuberculosis and 5 non-tuberculosis volunteers were selected as the study group and control group. Peripheral blood mononuclear cells(PBMC) of the two groups were collected as clinical samples. After total RNA was extracted, high-throughput sequencing technology was used to detect the differential expression of miRNA between the two groups.

Result

The clinical baseline data of 5 tuberculosis patients and 5 non-tuberculosis volunteers were collected, and the homogeneity and heterogeneity of 23 items between the two groups were obtained by statistical analysis. It was found that there were no significatly statistical differences in gender, age, smoking and drinking habits between the two groups. Body mass index (BMI), total cholesterol (TC), hemoglobin (Hb) albumin (ALB), globulin (GLB) and total protein (TP) in the study group were lower than those in the control group with significatly statistical differences(P<0.05). A total of 1560 miRNAs were screened out by miRNA sequencing. Through stratified cluster and comprehensive volcanic map analysis, 23 miRNAs with the most significant (P<0.05) differences were found in the case group, among which 15 were down-regulated(∣LOG2FC∣>1) and 8 were up-regulated(FC>1). In short, Combined with bioinformatics predictions, two miRNAs targeted VDR that differentially expressed in tuberculosis patients were screened out: hsa-miR-326(P<0.05、FC=1.37)、hsa-miR-654-5p(P<0.05、∣LOG2FC∣=1.06).

Conclusion

These two differentially expressed miRNAs mentioned abovemay be potential diagnostic markers and new therapeutic targets for tuberculosis.This found provides a new strategy and feasible direction for the prevention and treatment of Tuberculosis.

Key words: Tuberculosis, microRNA, Vitamin D, High-throughput sequencing, Bioinformatics

表1 研究组和对照组临床资料比较

临床资料	研究组(n＝5)	对照组(n＝5)	P值
年龄(岁)	44.2±9.24	51.60±20.29	0.491
性别[男(%)]	100.00	100.00	1.000
身高(cm)	165.6±5.86	162.8±11.54	0.642
体重(kg)	55.5±5.77	63.1±14.09	0.242
体重指数(BMI)	20.19±0.79	23.53±3.2	0.036
吸烟史	0.8±0.45	0.2±0.45	0.067
饮酒史	0.2±0.45	0.4±0.55	0.545
WBC(10⁹/L)	6.442±1.52	6.93±1.71	0.641
Hb(g/L)	114±15.24	148.60±27.64	0.042
PLT(10⁹)	297.6±86.11	246.40±74.84	0.345
TC(mmol/L)	2.72±0.63	5.12±0.78	0.001
TG(mmol/L)	0.99±0.24	2.10±1.74	0.197
HDL(mmol/L)	1.13±0.20	1.32±0.18	0.147
LDL(mmol/L)	1.91±0.25	2.69±0.82	0.077
ALT(IU/L)	17.4±14.10	27.90±9.99	0.211
AST(IU/L)	26.40±10.78	23.24±3.86	0.554
ALB(g/L)	35.9±5.78	51.98±3.38	0.001
GLB(g/L)	24.26±1.91	27.88±1.51	0.010
TP(g/L)	60.16±4.78	79.86±4.10	0.000
Cr(μmol/L)	63.54±12.96	77.42±18.29	0.204
BUN(mmol/L)	4.92±0.69	5.18±2.00	0.790
TBILI(μmol/L)	13.62±4.23	15.74±4.94	0.487
GLU(mmol/L)	7.14±4.16	4.96±0.82	0.283

表1 研究组和对照组临床资料比较

临床资料	研究组(n＝5)	对照组(n＝5)	P值
年龄(岁)	44.2±9.24	51.60±20.29	0.491
性别[男(%)]	100.00	100.00	1.000
身高(cm)	165.6±5.86	162.8±11.54	0.642
体重(kg)	55.5±5.77	63.1±14.09	0.242
体重指数(BMI)	20.19±0.79	23.53±3.2	0.036
吸烟史	0.8±0.45	0.2±0.45	0.067
饮酒史	0.2±0.45	0.4±0.55	0.545
WBC(10⁹/L)	6.442±1.52	6.93±1.71	0.641
Hb(g/L)	114±15.24	148.60±27.64	0.042
PLT(10⁹)	297.6±86.11	246.40±74.84	0.345
TC(mmol/L)	2.72±0.63	5.12±0.78	0.001
TG(mmol/L)	0.99±0.24	2.10±1.74	0.197
HDL(mmol/L)	1.13±0.20	1.32±0.18	0.147
LDL(mmol/L)	1.91±0.25	2.69±0.82	0.077
ALT(IU/L)	17.4±14.10	27.90±9.99	0.211
AST(IU/L)	26.40±10.78	23.24±3.86	0.554
ALB(g/L)	35.9±5.78	51.98±3.38	0.001
GLB(g/L)	24.26±1.91	27.88±1.51	0.010
TP(g/L)	60.16±4.78	79.86±4.10	0.000
Cr(μmol/L)	63.54±12.96	77.42±18.29	0.204
BUN(mmol/L)	4.92±0.69	5.18±2.00	0.790
TBILI(μmol/L)	13.62±4.23	15.74±4.94	0.487
GLU(mmol/L)	7.14±4.16	4.96±0.82	0.283

图1 10例样本高通量测序；注：A：为样本中miRNAs表达分为上调、下调和没有显著差异；B：为所有miRNAs差异表达谱FC>2的68条miRNAs在各个样本中的表达情况，以热图表示

表2 肺结核病患者差异表达显著的miRNAs

编　号	miRNA名称	miRNA序列	上调/下调	倍数(FC)	倍数(log2FC)	P值(T检验)
1	hsa-miR-1291_L+1R+1	GTGGCCCTGACTGAAGACCAGCAGTT	up	3.91	1.97	0.004
2	hsa-miR-27a-3p_R-1	TTCACAGTGGCTAAGTTCCG	up	1.37	0.45	0.006
3	hsa-miR-339-3p_R-2	TGAGCGCCTCGACGACAGAGC	up	1.52	0.61	0.016
4	hsa-miR-326_R+1	CCTCTGGGCCCTTCCTCCAGT	up	1.37	0.45	0.021
5	hsa-mir-6516-p3	TGTATGATACTGCAAACAGGA	up	3.13	1.65	0.034
6	hsa-miR-301a-3p	CAGTGCAATAGTATTGTCAAAGC	up	6.26	2.65	0.037
7	hsa-miR-30b-5p	TGTAAACATCCTACACTCAGCT	up	1.46	0.55	0.046
8	hsa-miR-30d-3p	CTTTCAGTCAGATGTTTGCTGC	up	2.9	1.54	0.047
9	hsa-miR-432-5p	TCTTGGAGTAGGTCATTGGGTGG	down	0.4	-1.34	0.000
10	hsa-miR-134-5p	TGTGACTGGTTGACCAGAGGGG	down	0.46	-1.11	0.001
11	hsa-miR-485-5p_R+1	AGAGGCTGGCCGTGATGAATTCG	down	0.5	-1.01	0.008
12	hsa-miR-4667-3p_R+1	TCCCTCCTTCTGTCCCCACAGT	down	0.27	-1.91	0.011
13	hsa-miR-127-3p	TCGGATCCGTCTGAGCTTGGCT	down	0.43	-1.21	0.012
14	hsa-miR-433-3p	ATCATGATGGGCTCCTCGGTGT	down	0.44	-1.18	0.012
15	hsa-miR-493-5p	TTGTACATGGTAGGCTTTCATT	down	0.47	-1.08	0.012
16	hsa-miR-382-5p	GAAGTTGTTCGTGGTGGATTCG	down	0.47	-1.1	0.014
17	hsa-miR-323a-3p_L+1	GCACATTACACGGTCGACCTCT	down	0.48	-1.07	0.018
18	hsa-miR-431-5p_R-1	TGTCTTGCAGGCCGTCATGC	down	0.4	-1.33	0.018
19	hsa-miR-654-5p	TATGTCTGCTGACCATCACC	down	0.48	-1.06	0.020
20	hsa-miR-941	CACCCGGCTGTGTGCACATGTGC	down	0.29	-1.81	0.021
21	hsa-miR-409-3p	GAATGTTGCTCGGTGAACCCCT	down	0.49	-1.03	0.022
22	hsa-miR-758-3p_R-1	TTTGTGACCTGGTCCACTAAC	down	0.5	-1.01	0.032
23	hsa-miR-550a-3-5p_R+1	AGTGCCTGAGGGAGTAAGAGA	down	0.23	-2.11	0.048

表2 肺结核病患者差异表达显著的miRNAs

编　号	miRNA名称	miRNA序列	上调/下调	倍数(FC)	倍数(log2FC)	P值(T检验)
1	hsa-miR-1291_L+1R+1	GTGGCCCTGACTGAAGACCAGCAGTT	up	3.91	1.97	0.004
2	hsa-miR-27a-3p_R-1	TTCACAGTGGCTAAGTTCCG	up	1.37	0.45	0.006
3	hsa-miR-339-3p_R-2	TGAGCGCCTCGACGACAGAGC	up	1.52	0.61	0.016
4	hsa-miR-326_R+1	CCTCTGGGCCCTTCCTCCAGT	up	1.37	0.45	0.021
5	hsa-mir-6516-p3	TGTATGATACTGCAAACAGGA	up	3.13	1.65	0.034
6	hsa-miR-301a-3p	CAGTGCAATAGTATTGTCAAAGC	up	6.26	2.65	0.037
7	hsa-miR-30b-5p	TGTAAACATCCTACACTCAGCT	up	1.46	0.55	0.046
8	hsa-miR-30d-3p	CTTTCAGTCAGATGTTTGCTGC	up	2.9	1.54	0.047
9	hsa-miR-432-5p	TCTTGGAGTAGGTCATTGGGTGG	down	0.4	-1.34	0.000
10	hsa-miR-134-5p	TGTGACTGGTTGACCAGAGGGG	down	0.46	-1.11	0.001
11	hsa-miR-485-5p_R+1	AGAGGCTGGCCGTGATGAATTCG	down	0.5	-1.01	0.008
12	hsa-miR-4667-3p_R+1	TCCCTCCTTCTGTCCCCACAGT	down	0.27	-1.91	0.011
13	hsa-miR-127-3p	TCGGATCCGTCTGAGCTTGGCT	down	0.43	-1.21	0.012
14	hsa-miR-433-3p	ATCATGATGGGCTCCTCGGTGT	down	0.44	-1.18	0.012
15	hsa-miR-493-5p	TTGTACATGGTAGGCTTTCATT	down	0.47	-1.08	0.012
16	hsa-miR-382-5p	GAAGTTGTTCGTGGTGGATTCG	down	0.47	-1.1	0.014
17	hsa-miR-323a-3p_L+1	GCACATTACACGGTCGACCTCT	down	0.48	-1.07	0.018
18	hsa-miR-431-5p_R-1	TGTCTTGCAGGCCGTCATGC	down	0.4	-1.33	0.018
19	hsa-miR-654-5p	TATGTCTGCTGACCATCACC	down	0.48	-1.06	0.020
20	hsa-miR-941	CACCCGGCTGTGTGCACATGTGC	down	0.29	-1.81	0.021
21	hsa-miR-409-3p	GAATGTTGCTCGGTGAACCCCT	down	0.49	-1.03	0.022
22	hsa-miR-758-3p_R-1	TTTGTGACCTGGTCCACTAAC	down	0.5	-1.01	0.032
23	hsa-miR-550a-3-5p_R+1	AGTGCCTGAGGGAGTAAGAGA	down	0.23	-2.11	0.048

图2 miRNAs功能及相似性分析；注：A:经过对比，33条miRNAs中，有显著相关性的miRNA有22条；B：22条miRNAs与细胞重编程、细胞分化等功能有密切联系；C：21条miRNAs参与的相对应生物学过程

表3 可能靶向VDR的miRNAs初步筛选结果

编　号	miRNA名称	3′非翻译区位置	种子匹配数	上下文得分
1	hsa-miR-654-5p	491-498	8mer	99
2	hsa-miR-541-3p	491-498	8mer	99
3	hsa-miR-302a-3p	3157-3164	8mer	98
4	hsa-miR-302b-3p	3157-3164	8mer	98
5	hsa-miR-302d-3p	3157-3164	8mer	98
6	hsa-miR-372-3p	3157-3164	8mer	98
7	hsa-miR-373-3p	3157-3164	8mer	98
8	hsa-miR-520e	3157-3164	8mer	98
9	hsa-miR-520a-3p	3157-3164	8mer	98
10	hsa-miR-520b	3157-3164	8mer	98
11	hsa-miR-520c-3p	3157-3164	8mer	98
12	hsa-miR-520d-3p	3157-3164	8mer	98
13	hsa-miR-532-3p	1859-1866	8mer	98
14	hsa-miR-302e	3157-3164	8mer	98
15	hsa-miR-556-3p	3130-3137	8mer	97
16	hsa-miR-10a-5p	1694-1701	8mer	95
17	hsa-miR-10b-5p	1694-1701	8mer	95
18	hsa-miR-3619-5p	3052-3059	8mer	95
19	hsa-miR-1913	251-258	8mer	87
20	hsa-miR-3194-5p	2937-2943	7mer-m8	84
21	hsa-miR-520d-5p	2605-2612	8mer	80
22	hsa-miR-4640-5p	2638-2644	7mer-m8	80
23	hsa-miR-2467-3p	115-121	7mer-m8	79
24	hsa-miR-524-5p	2605-2612	8mer	78
25	hsa-miR-326	285-292	8mer	76
26	hsa-miR-4726-5p	2638-2644	7mer-m8	70
27	hsa-miR-3918	2534-2540	7mer-m8	68
28	hsa-miR-324-3p	1081-1087	7mer-m8	62
29	hsa-miR-761	316-322	7mer-1A	45
30	hsa-miR-214-3p	2542-2548	7mer-m8	43
31	hsa-miR-330-5p	1058-1064	7mer-m8	39
32	hsa-miR-515-5p	902-908	7mer-1A	21
33	hsa-miR-519e-5p	902-908	7mer-1A	21

表3 可能靶向VDR的miRNAs初步筛选结果

编　号	miRNA名称	3′非翻译区位置	种子匹配数	上下文得分
1	hsa-miR-654-5p	491-498	8mer	99
2	hsa-miR-541-3p	491-498	8mer	99
3	hsa-miR-302a-3p	3157-3164	8mer	98
4	hsa-miR-302b-3p	3157-3164	8mer	98
5	hsa-miR-302d-3p	3157-3164	8mer	98
6	hsa-miR-372-3p	3157-3164	8mer	98
7	hsa-miR-373-3p	3157-3164	8mer	98
8	hsa-miR-520e	3157-3164	8mer	98
9	hsa-miR-520a-3p	3157-3164	8mer	98
10	hsa-miR-520b	3157-3164	8mer	98
11	hsa-miR-520c-3p	3157-3164	8mer	98
12	hsa-miR-520d-3p	3157-3164	8mer	98
13	hsa-miR-532-3p	1859-1866	8mer	98
14	hsa-miR-302e	3157-3164	8mer	98
15	hsa-miR-556-3p	3130-3137	8mer	97
16	hsa-miR-10a-5p	1694-1701	8mer	95
17	hsa-miR-10b-5p	1694-1701	8mer	95
18	hsa-miR-3619-5p	3052-3059	8mer	95
19	hsa-miR-1913	251-258	8mer	87
20	hsa-miR-3194-5p	2937-2943	7mer-m8	84
21	hsa-miR-520d-5p	2605-2612	8mer	80
22	hsa-miR-4640-5p	2638-2644	7mer-m8	80
23	hsa-miR-2467-3p	115-121	7mer-m8	79
24	hsa-miR-524-5p	2605-2612	8mer	78
25	hsa-miR-326	285-292	8mer	76
26	hsa-miR-4726-5p	2638-2644	7mer-m8	70
27	hsa-miR-3918	2534-2540	7mer-m8	68
28	hsa-miR-324-3p	1081-1087	7mer-m8	62
29	hsa-miR-761	316-322	7mer-1A	45
30	hsa-miR-214-3p	2542-2548	7mer-m8	43
31	hsa-miR-330-5p	1058-1064	7mer-m8	39
32	hsa-miR-515-5p	902-908	7mer-1A	21
33	hsa-miR-519e-5p	902-908	7mer-1A	21

1	Wallis Robert S, Maeurer Markus, Mwaba Peter, et al. Tuberculosis-advances in development of new drugs, treatment regimens, host-directed therapies, and biomarkers[J]. Lancet Infect Dis, 2016, 16(4): e34-46.
2	White JH. Vitamin D metabolism and signaling in the immune system [J]. Reviews Endocrine Metabolic Disorders, 2012, 13(1): 21-29.
3	Wingfield Tom, Schumacher Samuel G, Sandhu Gurjinder, et al. The seasonality of tuberculosis, sunlight, vitamin D, and household crowding[J]. J Infect Dis, 2014, 210(5): 774-783.
4	Panda Sudhasini, Tiwari Ambrish, Luthra Kalpana, et al. Status of vitamin D and the associated host factors in pulmonary tuberculosis patients and their household contacts: A cross sectional study[J]. J Steroid Biochem Molecular Biology, 2019, 193: 105419.
5	Wallis RS, Zumla A. Vitamin D as Adjunctive Host-Directed Therapy in Tuberculosis: A Systematic Review[J]. Open Forum Infectious Diseases, 2016, 3(3): 151.
6	Campbell MJ, Trump DL. Vitamin D Receptor Signaling and Cancer[J]. Endocrinology and Metabolism Clinics of North America, 2017, 46(4): 1009-1038.
7	Yang T, B Ge. miRNAs in immune responses to Mycobacterium tuberculosis infection[J]. Cancer Letters, 2018, 431: 22-30.
8	Jadideslam G, Ansarin K, Sakhinia E, et al. The MicroRNA-326: Autoimmune diseases, diagnostic biomarker, and therapeutic target[J]. J Cell Physiol, 2018, 233(12): 9209-9222.
9	Singh, P．K., et al., VDR regulation of microRNA differs across prostate cell models suggesting extremely flexible control of transcription[J]. Epigenetics, 2015, 10(1): 40-49.
10	Xing He, Yue Sun, Nanhang Lei, et al. MicroRNA-351 promotes schistosomiasis-induced hepatic fibrosis by targeting the vitamin D receptor[J]. Proceedings of the National Academy of Sciences, 2018, 115(1): 180-185.
11	Kong Fanjing, Chenxiang Du, Wang Yu. MicroRNA-9 affects isolated ovarian granulosa cells proliferation and apoptosis via targeting vitamin D receptor[J]. Molecular and Cellular Endocrinology, 2019, 486(15): 18-24.
12	Padi Sathish KR, Zhang Qunshu, Rustum Youcef M, et al. MicroRNA- 627 Mediates the Epigenetic Mechanisms of Vitamin D to Suppress Proliferation of Human Colorectal Cancer Cells and Growth of Xenograft Tumors in Mice[J]. Gastroenterology, 2013, 145(2): 437-446.
13	Wang Min, Kong Weimin, Biyu He, et al. Vitamin D and the promoter methylation of its metabolic pathway genes in association with the risk and prognosis of tuberculosis[J]. Clinical Epigenetics, 2018, 10(1): 118.
14	Ouimet Mireille, Koster Stefan, Sakowski Erik, et al. Mycobacterium tuberculosis induces the miR-33 locus to reprogram autophagy and host lipid metabolism[J]. Nat Immunol, 2016, 17(6): 677-86.
15	Feng Liu, Chen Jianxia, Wang Peng, et al. MicroRNA-27a controls the intracellular survival of Mycobacterium tuberculosis by regulating calcium-associated autophagy[J]. Nat Commun, 2018, 9(1): 4295.
16	刘小利，刘　涛. 新版肺结核诊断标准解读[J]. 中华灾害救援医学，2018, 6(4): 181-185.
17	Collaborative Group for the Meta-Analysis of Individual Patient Data in MDR-TB treatment-2017; Ahmad Nafees, Ahuja Shama D, et al. Treatment correlates of successful outcomes in pulmonary multidrug-resistant tuberculosis: an individual patient data meta-analysis[J]. Lancet, 2018, 392(10150): 821-834.
18	任成山，林　辉，杨仕明. 结核病的流行特征与耐多药的窘迫及其策略[J/CD]. 中华肺部疾病杂志(电子版), 2019, 12(3): 269-274.
19	Baek Seung Don, Jeung Soomin, Kang Jae-Young. Nutritional Adequacy and Latent Tuberculosis Infection in End-Stage Renal Disease Patients[J]. Nutrients, 2019, 11(10): 2299.
20	Sinha Pranay, Hochberg Natasha S. Crystal ball: the yesterday and tomorrow of tuberculosis[J]. Environmental Microbiology Reports, 2019, 11(1): 41-44.
21	Ralph AP, Lucas RM, Norval M. Vitamin D and solar ultraviolet radiation in the risk and treatment of tuberculosis[J]. Lancet Infect Dis, 2013, 13(1): 77-88.

[1]	闫文, 谢兴文, 顾玉彪, 雷宁波, 马成, 于文霞, 高亚雄, 张磊. 微小RNA与全膝关节置换术后深静脉血栓的研究进展[J]. 中华关节外科杂志(电子版), 2023, 17(06): 842-846.
[2]	李聪, 徐艳, 吴铭, 丁瑞东, 王军. 极低出生体重儿出生时血清25-羟维生素D水平与其生后早期喂养不耐受关系的临床分析[J]. 中华妇幼临床医学杂志(电子版), 2023, 19(03): 309-314.
[3]	李越洲, 张孔玺, 李小红, 商中华. 基于生物信息学分析胃癌中PUM的预后意义[J]. 中华普通外科学文献(电子版), 2023, 17(06): 426-432.
[4]	马伟强, 马斌林, 吴中语, 张莹. microRNA在三阴性乳腺癌进展中发挥的作用[J]. 中华普外科手术学杂志(电子版), 2024, 18(01): 111-114.
[5]	李婷, 张琳. 血清脂肪酸代谢物及维生素D水平与结直肠癌发生的关系研究[J]. 中华普外科手术学杂志(电子版), 2023, 17(06): 661-665.
[6]	彭雨诗, 苗芸, 严紫嫣. 宏基因组高通量测序诊断肾移植术后华支睾吸虫感染一例[J]. 中华移植杂志(电子版), 2023, 17(05): 297-299.
[7]	方道成, 胡媛媛. 钙和维生素D与肾结石形成关系的研究进展[J]. 中华腔镜泌尿外科杂志(电子版), 2023, 17(06): 653-656.
[8]	张圣平, 邓琼, 张颖, 张建文, 梁辉, 王铸. 孤儿核受体HNF4α在肾透明细胞癌中的表达及意义[J]. 中华腔镜泌尿外科杂志(电子版), 2023, 17(06): 627-632.
[9]	唐国军, 洪余德, 赵崇玉, 李辽源. 基于TCGA数据库Wnt相关长链非编码RNA构建肾乳头状细胞癌预后模型[J]. 中华腔镜泌尿外科杂志(电子版), 2023, 17(03): 270-275.
[10]	邱静, 黄庆. HJURP在肺腺癌组织中高表达并与患者不良预后相关性[J]. 中华肺部疾病杂志(电子版), 2023, 16(04): 495-499.
[11]	谭玲芳, 周克兵. 基于生物信息学整合鉴定与支气管哮喘相关的潜在诊断生物标志物[J]. 中华肺部疾病杂志(电子版), 2023, 16(03): 329-334.
[12]	张维志, 刘连新. 基于生物信息学分析IPO7在肝癌中的表达及意义[J]. 中华肝脏外科手术学电子杂志, 2023, 12(06): 694-701.
[13]	陈安, 冯娟, 杨振宇, 杜锡林, 柏强善, 阴继凯, 臧莉, 鲁建国. 基于生物信息学分析CCN4在肝细胞癌中表达及其临床意义[J]. 中华肝脏外科手术学电子杂志, 2023, 12(06): 702-707.
[14]	王苏贵, 皇立媛, 姜福金, 吴自余, 张先云, 李强, 严大理. 异质性细胞核核糖蛋白A2B1在前列腺癌中的作用及其靶向中药活性成分筛选研究[J]. 中华临床医师杂志(电子版), 2023, 17(06): 731-736.
[15]	张敏洁, 王雅晳, 段莎莎, 施依璐, 付文艳, 赵海玥, 张小杉. 基于GEO数据库和生物信息学分析筛选大鼠心肌缺血再灌注损伤相关潜在通路和靶点[J]. 中华临床医师杂志(电子版), 2023, 17(04): 438-445.

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

A study of microRNA Prescreening that targeted and regulated Vitamin D rceptor in tuberculosis patients

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

A study of microRNA Prescreening that targeted and regulated Vitamin D rceptor in tuberculosis patients