Objectives: Dendritic cells are one of the first host cells that cryptococcus encounters. However, the correlations among cryptococcus, dendritic cells, and long noncoding RNA remain unclear. This study was undertaken to investigate the effects of long noncoding RNAs on dendritic cells with cryptococcus infection.
Materials and Methods: We treated dendritic cells with cryptococcus and then detected expression of CD80, CD86, and major histocompatibility complex class II in dendritic cells with a real-time fluorescent quantitative polymerase chain reaction assay. We used next-generation sequencing and bioinformatics analysis to determine the competitive endogenous RNA mechanisms, confirmed via real-time polymerase chain reaction, dual luciferase reporter, and RNA-binding protein immunoprecipitation assays. Results: After treatment of dendritic cells with 1 × 108 CFU/mL cryptococcus for 12 hours, dendritic cell viability was normal, whereas mRNA expression levels of CD80, CD86, and major histocompatibility complex class II in dendritic cells were substantially increased. With next-generation sequencing, we discovered 4 small nucleolar RNA host genes (snhg1, snhg3, snhg4, and snhg16) in cryptococcus-treated dendritic cells compared with wild-type dendritic cells. Bioinformatics analysis combined with real-time polymerase chain reaction led us to speculate that cryptococcus may affect the maturation and apoptosis of dendritic cells by regulating snhg1-miR-145a-3p-Bcl2. Further polymerase chain reaction, dual luciferase reporter, and RNA-binding protein immunoprecipitation experi-ments revealed that snhg1 acted as a sponge for miR-145a-3p to inhibit the expression of miR-145a-3p and that miR-145a-3p promoted the expression of Bcl2 by directly targeting the 3?-UTR of Bcl2. Functional recovery experiments showed that cryptococcus promoted the maturation and apoptosis and inhibited the proliferation of dendritic cells through the snhg1-Bcl2 pathway.
Conclusions: This study lays a foundation for the further understanding of the pathogenic role of snhg1-miR-145a-3p-Bcl2 axis in cryptococcosis.

Key words : Long noncoding RNA, MicroRNA, Small nucleolar RNA host genes

Introduction

Cryptococcosis is a globally distributed and invasive fungal infection and can cause cryptococcal menin-goencephalitis in healthy and immunocompromising hosts through inhalation and subsequent pulmonary sensation.^1-3 At present, continuous and longitudinal antifungal therapy is the main treatment method for cryptococcal meningitis. However, this treatment has not yielded significant clinical results.

Dendritic cells (DCs) regulate innate and adaptive immune responses and are considered as the most effective antigen-presenting cells.⁴ Dendritic cells recognize the pathogen-associated molecular patterns that are shed by cryptococcus; activated DCs promote the secretion of interferon-γ, interleukin 12, and interleukin 23 by inducing the polarization of CD4+ T cells to T-helper cell 1, ultimately controlling fungal infection.¹ Therefore, DCs are crucial in controlling cryptococcosis infection.

One of the factors that affect the interaction between DCs and T cells is the maturation state of DCs.⁴ Long noncoding RNAs (lncRNAs) regulate the biological functions of cells through various ways, such as competitively binding micro-RNAs (miRNAs), directly binding proteins, and regulating chromatin remodeling.⁵ With the use of whole-genome sequencing, Joslyn and colleagues⁶ proposed that 588 lncRNAs regulated by Toll-like receptor 7 and type I interferon may significantly change the maturation of plasmacytoid DCs. Wang and colleagues⁷ reported that lncRNAs induce the differentiation, maturation, and apoptosis of DCs by directly binding STAT3 to activate downstream signals of STAT3. Therefore, lncRNA is an important regulator of the cell function of DCs.

A total of 263 upregulated and 234 downregulated lncRNAs have been identified in patients with cryptococcal meningitis,⁸ suggesting that cryptoco-ccosis may regulate the differential expression of lncRNAs. However, whether cryptococcosis regulates the differential expression of lncRNA in DCs is still unknown; whether these differentially expressed lncRNAs affect the maturation and apoptosis of DCs is the focus of our study.

Materials and Methods

Study design
In this experimental study, we first compared differentially expressed genes in peripheral blood from patients with cryptococcal meningitis and from healthy controls at the clinical level using next-generation sequencing. Based on the differentially expressed genes and bioinformatics analysis, we explored the potential mechanisms involved in cryptococcus. Next, we verified the underlying mechanisms involved in cryptococcus and the related cell functions at the cell level (Figure 1).

Participants
Researchers collected 3 to 5 mL of peripheral blood from 10 patients with cryptococcal meningitis (male, 44 ± 15.46 years) and 10 healthy controls (male, 39.1 ± 8.61 years) from January 2021 to June 2021 at the 9th Hospital of Shanghai Jiaotong University. The diagnosis of cryptococcal meningitis was based on the detection of cryptococcal antigen by latex agglutination of cerebrospinal fluid. All experiments were conducted with written informed consent from participants. This study was approved by the 9th Hospital of Shanghai Jiaotong University Hospital Ethics Committee.

Next-generation sequencing of peripheral blood
The PureLink total blood RNA kit (K156001, Thermo Fisher Scientific) was used to extract total RNA from blood samples from the 10 patients with cryptococcal meningitis and the 10 healthy controls. The TaqMan reverse transcription reagent (N8080234, Thermo Fisher Scientific) was used to reverse total RNA into cDNA. The transcriptome was sequenced using Agilent-048908 8 × 60K platform. The microarray and data collection procedures were conducted by researchers from Shanghai Jike Biochemistry.

Cell culture
Mouse bone marrow-derived DCs were purchased from Beijing Beina Chuanglian Biotechnology Research Institute, cultured in DMEM medium (L110KJ, Shanghai BasalMedia Technologies), and supplemented with 10% of fetal bovine serum and 1% of penicillin-streptomycin (15070063, Thermo Fisher Scientific) at 37 °C and 5% CO2 in a humid incubator. We cultured DCs for 12 or 24 hours with 1 × 107, 1 × 108, and 1 × 109 CFU/mL cryptococcus.

Next-generation sequencing
After DCs cells were cultured with or without 1 × 108 CFU/mL cryptococcus for 12 hours, Nanodrop2000 was used to detect the concentration and purity of the extracted RNA, with 3 samples in each group. We used the TruSeqTM Wi-Fi total RNA library prep kit to build the library and detected gene expression in each group with Illumina HiSeq.

Real-time quantitative polymerase chain reaction
Total RNA or miRNA in cells was extracted using Trizol reagent (15596026, Invitrogen) or with the miRNA extraction kit (RC201, Vazyme), and cDNA was synthesized using the TaqMan reverse trans-cription reagent (N8080234, Thermo Fisher Scientific) or the miRNA reverse kit (218161, Qiagen). According to the corresponding primers (Table 1), we detected gene expression with the Power SYBR green polymerase chain reaction (PCR) master kit (4368708, Applied Biosystems) method. The primers of miRNA included ACTCAAAATGGAGGCCCTATC for mmu-miR-294-5p, ACTCAAAACCTGGCGGC for mmu-miR-292b-5p, and TCCTGGAAATACT GTTCTTGAAA for mmu-miR-145a-3p. Finally, we used 2-??Ct to calculate the relative expression of genes.

Cell transfection and treatment
For transfection, we seeded DCs in 6-well plates and transfected cells with corresponding agents using lipofectamine 3000 reagent (L3000-015, Invitrogen) when the cells reached 70% confluence. Small interfering RNA (siRNA)-snhg1-149, siRNA-snhg1-303, siRNA-snhg1-418, miR-145a-3p mimic, and their controls were designed and synthesized by Ribobio Biotechnology. We also used DCs for follow-up experiments after 48 hours of transfection. For cell treatment, 250 nM Bcl2 inhibitor (ABT-199, HY-15531, MedChemExpress) was used to inhibit the expression of Bcl2 in DCs, and follow-up experiments were conducted after 48 hours of treatment.

Luciferase report assay
The wild-type reporter construct pmirGLO-Bcl2 or the mutant reporter construct pmirGLO-Bcl2-mut was cotransfected with miR-145a-3p mimic or miR-negative control in DCs. After transfection for 48 hours, firefly luciferase levels were measured using a Dual-Luciferase reporter assay system (Varioskan LUX, Thermo Fisher Scientific) and normalized to Renilla luciferase activity.

Western blot
We extracted protein from cells using RIPA buffer, with quantification using the BCA protein assay kit (C503021, Sankon Bioengineering). Protein was then isolated using sodium dodecyl-sulfate polyacrylamide gel electrophoresis. The primary antibodies used were Bcl2 polyclonal antibody (26593-1-AP, Proteintech), CD80/B7-1 monoclonal antibody (66406-1-Ig, Proteintech), CD86 polyclonal antibody (13395-1-AP, Proteintech), anti-CD40 (ab252428, Abcam), anti-major histocompatibility complex class II (MHC-II; ab139365, Abcam), and anti-CCR7 (ab32527, Abcam). The secondary antibodies were horseradish peroxidase-labeled goat anti-mouse IgG (A0216, Biyuntian Biotechnology) and horseradish peroxidase-labeled goat anti-rabbit IgG (A0208, Biyuntian Biotechnology).

RNA immunoprecipitation assay<br> We performed the RNA immunoprecipitation (RIP) assay as previously described.⁹ Briefly, the lysate of 2 × 10⁷ DCs were incubated with magnetic beads conjugated with mouse anti-Ago2 antibody (FNab00214, Wuhan FineTest Biotechnology). The immunoprecipitated RNAs were extracted, and the enrichment of snhg1 and miR-145a-3p was confirmed by real-time PCR (RT-PCR).

Cell counting kit-8
We used the cell counting kit 8 (CCK-8) assay, according to the manufacturer’s instructions, to measure cell proliferation. We seeded 5 × 10³ DCs in 96-well plates overnight and then added the corresponding drugs. We added 10 μL CCK-8 solution to each well and cultured them for 2 hours. Absorbance at 450 nm was determined with a microplate analyzer.

TUNEL experiment
In this study, we used terminal deoxynucleotidyl transferase-mediated dUTP nick end labeling (TUNEL) to detect cell apoptosis.¹⁰ The specific steps of the TUNEL experiment were as described previously.¹¹ Briefly, the cells were added with 100 μL of TDT enzyme reaction solution and reacted at 37 ? for 60 minutes, followed by treatment with100 μL of streptavidin-fluorescein labeling solution. The nucleus was restained with DAPI staining solution and reacted at room temperature for 10 minutes without light. Fluorescence mic-roscopy (excitation wavelengths of 450-500 nm, emission wavelengths of 515-565 nm) was used to detect the fluorescence of each group.

Statistical analyses
Data are shown as means ± SD. We analyzed data using 2-way analysis or the t-test; P < .05 was considered to be significant. We used the Pearson correlation coefficient for correlation analysis between genes, with P < .05 considered to be correlated.

Results

Conditions for the treatment of dendritic cells by cryptococcus
After DCs were treated with 1 × 10⁷ (low concen-tration), 1 × 10⁸ (medium concentration), or 1 × 10⁹ (high concentration) CFU/mL cryptococcus for 12 hours and 24 hours, RT-PCR was used to detect the expression levels of CD80, MHC-II, and CD86 mRNA in DCs. Compared with the control group, mRNA expression levels of CD80, CD86, and MHC-II were substantially increased (Figure 2A), but survival of DCs was normal (Figure 2, B and C) after treatment with the medium concentration of cryptococcus for 12 hours. After treatment of DCs with high concentration of cryptococcus for 24 hours, the mRNA expression levels of CD80, CD86, and MHC-II increased substantially (Figure 2A). In addition, the survival of DCs was substantially reduced (Figure 2, B and C). Therefore, the medium concentration of cryptococcus was used to treat DCs for 12 hours in subsequent experiments.

Screening of differentially expressed genes in dendritic cells treated with cryptococcus based on next-generation sequencing
Through next-generation sequencing, we found 21 differentially expressed lncRNAs in DCs treated with the medium concentration of cryptococcus for 12 hours (Figure 3A). Among the lncRNAs, we found 4 lncRNAs in the small nucleolar RNA host gene (snhg) family, namely snhg1, snhg3, snhg4, and snhg16. By using miRDB tools, we further predicted the targets of these lncRNAs, among which the miRNA target shared by “snhg1” and “snhg16” was mmu-miR-145a-3p and the miRNA targets shared by “snhg3” and “snhg4” were mmu-miR-292b-5p and mmu-miR-294-5p (Figure 3B). Through next-generation mRNA sequencing, we obtained 1027 differentially expressed mRNAs, including 495 upregulated mRNAs and 532 downregulated mRNAs in DCs treated with the medium concentration of cryptococcus for 12 hours (Figure 3C). Combined with our sequencing results, we further used the Targetscan (https://www.targetscan.org/mamm_31/) and the miWalk (https://mirwalk.umm.uni-heidelberg.de/) websites to predict the target mRNAs of mmu-miR-145a-3p (Figure 3D), mmu-miR-292b-5p (Figure 3E), and mmu-miR-294-5p (Figure 3F) to obtain mRNA that may be regulated by snhg1, snhg3, snhg4, and snhg16. Therefore, we constructed the upregulated competing endogenous RNAs (ceRNA) network (Figure 3G) and the downregulated ceRNA network (Figure 3H).

Further GO (Figure 4, A and B) and KEGG (Figure 4, C and D) analyses exhibited that these down-regulated mRNAs were remarkably enriched in the PI3K-Akt signaling pathway (MCC04151), the RAS signaling pathway (MCC04014), and the MAPK signaling pathway (MCC04010). Correlation analysis demonstrated that the expression trends of sngh1, sngh3, sngh4, and sngh16 were consistent. Specifically, the correlation between sngh16 and snhg4 was 0.97, the correlation between sngh3 and snhg4 was 1, and the correlation between sngh1 and snhg16 was 0.95 (Figure 4E). In addition, sngh1, sngh3, sngh4, and sngh16 had significant positive correlations with the downstream genes of MCC04151, MCC04014, and MCC04010 pathways, including Bcl2, Thbs1, Ppp2r1b, and Tgfb3 (Figure 4E). These results indicated that snhg1, snhg3, snhg4, and snhg16 may regulate the cell function of DCs by upregulating the expression of Bcl2, Thbs1, Ppp2r1b, and Tgfb3.

Cryptococcus regulates the competing endogenous RNA network snhg1-miR-145a-3p-Bcl2 in dendritic cells
With the use of RT-PCR, we found that, compared with the control group, after cryptococcus infection of DCs for 12 hours, expression levels of snhg1, snhg3, snhg4, and snhg16 in DCs were substantially decreased (Figure 5A), the expression of miR-145a-3p was greatly increased (Figure 5B), and the expression levels of Bcl2, Thbs1, Ppp2r1b, and Tgfb3 were decreased (Figure 5C), showing that these results were consistent with the sequencing results. Long noncoding RNAs often promote the expression of mRNA by inhibiting the expression of miRNA. Therefore, the expression results of miR-145a-3p are in line with expectations. Furthermore, the predicted results of bioinformatics analysis showed that miR-145a-3p may be the target of snhg1 and snhg16; compared with snhg16, the expression of snhg1 was lower; thus, snhg1 was selected for subsequent experiments.

Our RIP experiments showed that expression levels of miR-145a-3p and snhg1 in the AGO2 protein group were remarkably higher than that in the IgG group, indicating that snhg1 binds to miR-145a-3p (Figure 5D). The results of the dual luciferase experiment suggested that miR-145a-3p downre-gulates the luciferase of Bcl2. However, after the 3'-UTR mutation of Bcl2, this regulatory relationship disappeared, showing that miR-145a-3p binds to the 3'-UTR of Bcl2 (Figure 5E). These results showed that cryptococcus inhibits Bcl2 expression through the snhg1-miR-145a-3p axis.

Cryptococcus regulates the competing endogenous RNA network snhg1-miR-145a-3p-Bcl2 in dendritic cells
Dendritic cells were transiently transfected with siRNA-snhg1 for 48 hours, and the cells were collected. With RT-PCR, the expression level of snhg1 was shown to be substantially reduced and siRNA-418 had the best interference effects (Figure 6A). Our RT-PCR experiments further illustrated that the expression of Bcl2 mRNA was obviously reduced and that expression of miR-145a-3p was extremely increased after the interference of snhg1 expression (Figure 6B). Most importantly, Western blot (WB) experiments demonstrated that the expression level of Bcl2 protein was largely reduced after interfering with snhg1 expression (Figure 6C). These results indicated that snhg1 promotes the expression of Bcl2 by directly inhibiting the expression of miR-145a-3p.

The WB experiment was carried out to detect the protein expression of DC-related molecules CD40, CD80, CD86, MHC-II, and CCR7. Our results suggested that, compared with the control group, the expression levels of these proteins were substantially reduced in the siRNA-snhg1 group and the siRNA-snhg1 plus Bcl2 inhibitor group had more significant effects on the level of apoptosis than the siRNA-snhg1 group (Figure 7A). In our CCK-8 experiments to detect the viability of DCs, we found that, compared with the control group, the cell viability was significantly reduced in the siRNA-snhg1 group and the effects of siRNA-snhg1 plus Bcl2 inhibitor group (250nM ABT-199) on the viability of DCs were more significant than in the siRNA-snhg1 group (Figure 7B). Our TUNEL experiment showed that, compared with the control group, the level of apoptosis increased in the siRNA-snhg1 group and the siRNA-snhg1 + Bcl2 inhibitor group had more significant effects on the level of apoptosis than the siRNA-snhg1 group (Figure 7C). These results suggested that cryptococcus may inhibit the survival and promote the maturation and apoptosis of DCs through snhg1/miR-145a-3p/Bcl2, thereby reducing the host immune response.

Discussion

In this work, we characterized the biological role of cryptococcus in DCs, which inhibits the maturation of DCs and promotes the apoptosis of DCs by regulating the snhg1-miR-145a-3p-Bcl2 pathway.

Under the stimulation of antigen, DCs develop into mature DCs through a complicated developmental process.¹² In mature DCs, the expression of costimulatory molecules CD80 and CD86 increase and MHC-II is activated.^13,14 After we treated DCs with 1 × 108 CFU/mL cryptococcus for 12 hours, expression levels of CD80, MHC-II, and CD86 in DCs significantly increased, consistent with previous results.¹⁵ However, even after antifungal treatment, the infection and reinfection of cryptococcus in patients are still difficult to be solved clinically.¹⁶ Therefore, we speculated that cryptococcus may have a potential mechanism to inhibit DCs maturation during long-term infection.

Silencing NEAT1 has been shown to promote the tolerogenic phenotype of DCs through the miR-3076-3p-NLRP3 axis.¹⁷ Long noncoding RNAs in DCs regulates the growth, apoptosis, and immune response of DCs through the toll-like receptor 9/STAT3 signal.¹⁸ These data indicated that lncRNAs can regulate the cellular functions of DCs. From next-generation sequencing and RT-PCR, cryptococcus was shown to inhibit the expression of snhg1 in DCs. Our additional WB experiments revealed that silencing snhg1 inhibited the expression of CD80, CD86, MHC-II, and CCR7 in DCs, suggesting that silencing snhg1 inhibits the maturation of DCs. Mature DCs have also been reported to migrate to draining lymph nodes in a chemokine receptor CCR7-dependent manner.¹⁹ Therefore, silencing snhg1 may also inhibit the migration of mature DCs. Apoptosis plays a vital role in terms of regulating homeostasis and cell fate.²⁰ Cell function experiments displayed that silencing snhg1 promotes the apoptosis and inhibits the proliferation of DCs. These results indicated that silencing snhg1 inhibits the proliferation, maturation, and migration of DCs and promotes the apoptosis of DCs.

Combined with bioinformatics analysis, RT-PCR, next-generation sequencing, and luciferase and RIP experiments, we further clarified a ceRNA network of snhg1-miR-145a-3p-Bcl2 in DCs. Antiapoptotic protein plays an important role in the mechanism of mitochondrial apoptosis.^21,22 Through the TUNEL and CCK-8 experiments, it was obvious that Bcl2 inhibitors substantially promote the apoptosis and the proliferation of DCs, and this phenomenon was more significant in the siRNA-snhg1+Bcl2 inhibitor group. These results suggested that cryptococcus inhibits the proliferation of DCs and promotes the apoptosis of DCs through snhg1-miR-145a-3p-Bcl2. With the WB experiments, it was obvious that Bcl2 inhibitors inhibit the expression of CD80, CD86, MHC-II, and CCR7 in DCs, and the inhibition of these proteins was more significant in the siRNA-snhg1+Bcl2 inhibitor group. These results further showed that cryptococcus inhibits the maturation and migration of DCs through snhg1-miR-145a-3p-Bcl2.

Conclusions

Our study elucidated that snhg1-miR-145a-3p-Bcl2 is the potential mechanism by which cryptococcus regulates the maturation, proliferation, apoptosis, and migration of DCs. The upregulated expression of snhg1 in DCs may become a potential strategy for the treatment of cryptococcal infection.

References:

1. May RC, Stone NR, Wiesner DL, Bicanic T, Nielsen K. Cryptococcus: from environmental saprophyte to global pathogen. Nat Rev Microbiol. 2016;14(2):106-117. doi:10.1038/nrmicro.2015.6
   CrossRef - PubMed
2. Ergin C, Sengul M, Aksoy L, et al. Cryptococcus neoformans recovered from olive trees (Olea europaea) in Turkey reveal allopatry with African and South American lineages. Front Cell Infect Microbiol. 2019;9:384. doi:10.3389/fcimb.2019.00384
   CrossRef - PubMed
3. Franco-Paredes C, Womack T, Bohlmeyer T, et al. Management of Cryptococcus gattii meningoencephalitis. Lancet Infect Dis. 2015;15(3):348-355. doi:10.1016/S1473-3099(14)70945-4
   CrossRef - PubMed
4. Waisman A, Lukas D, Clausen BE, Yogev N. Dendritic cells as gatekeepers of tolerance. Semin Immunopathol. 2017;39(2):153-163. doi:10.1007/s00281-016-0583-z
   CrossRef - PubMed
5. Jarroux J, Morillon A, Pinskaya M. History, discovery, and classification of lncRNAs. Adv Exp Med Biol. 2017;1008:1-46. doi:10.1007/978-981-10-5203-3_1
   CrossRef - PubMed
6. Joslyn RC, Forero A, Green R, Parker SE, Savan R. Long noncoding RNA signatures induced by Toll-like receptor 7 and type I interferon signaling in activated human plasmacytoid dendritic cells. J Interferon Cytokine Res. 2018;38(9):388-405. doi:10.1089/jir.2018.0086
   CrossRef - PubMed
7. Wang P, Xue Y, Han Y, et al. The STAT3-binding long noncoding RNA lnc-DC controls human dendritic cell differentiation. Science. 2014;344(6181):310-313. doi:10.1126/science.1251456
   CrossRef - PubMed
8. Zhang L, Fang WJ, Zhang KM, et al. Long noncoding RNA expression profile from cryptococcal meningitis patients identifies DPY19L1p1 as a new disease marker. CNS Neurosci Ther. 2019;25(6):772-782. doi:10.1111/cns.13109
   CrossRef - PubMed
9. Hu YP, Jin YP, Wu XS, et al. Correction to: LncRNA-HGBC stabilized by HuR promotes gallbladder cancer progression by regulating miR-502-3p/SET/AKT axis. Mol Cancer. 2021;20(1):110. doi:10.1186/s12943-021-01386-8
   CrossRef - PubMed
10. Kyrylkova K, Kyryachenko S, Leid M, Kioussi C. Detection of apoptosis by TUNEL assay. Methods Mol Biol. 2012;887:41-47. doi:10.1007/978-1-61779-860-3_5
    CrossRef - PubMed
11. Zhao W, Geng D, Li S, Chen Z, Sun M. LncRNA HOTAIR influences cell growth, migration, invasion, and apoptosis via the miR-20a-5p/HMGA2 axis in breast cancer. Cancer Med. 2018;7(3):842-855. doi:10.1002/cam4.1353
    CrossRef - PubMed
12. Gil-Torregrosa BC, Lennon-Dumenil AM, Kessler B, et al. Control of cross-presentation during dendritic cell maturation. Eur J Immunol. 2004;34(2):398-407. doi:10.1002/eji.200324508
    CrossRef - PubMed
13. Reis e Sousa C. Dendritic cells in a mature age. Nat Rev Immunol. 2006;6(6):476-483. doi:10.1038/nri1845
    CrossRef - PubMed
14. Vargas P, Maiuri P, Bretou M, et al. Innate control of actin nucleation determines two distinct migration behaviours in dendritic cells. Nat Cell Biol. 2016;18(1):43-53. doi:10.1038/ncb3284
    CrossRef - PubMed
15. Pietrella D, Corbucci C, Perito S, Bistoni G, Vecchiarelli A. Mannoproteins from Cryptococcus neoformans promote dendritic cell maturation and activation. Infect Immun. 2005;73(2):820-827. doi:10.1128/IAI.73.2.820-827.2005
    CrossRef - PubMed
16. Bongomin F, Oladele RO, Gago S, Moore CB, Richardson MD. A systematic review of fluconazole resistance in clinical isolates of Cryptococcus species. Mycoses. 2018;61(5):290-297. doi:10.1111/myc.12747
    CrossRef - PubMed
17. Zhang M, Zheng Y, Sun Y, et al. Knockdown of NEAT1 induces tolerogenic phenotype in dendritic cells by inhibiting activation of NLRP3 inflammasome. Theranostics. 2019;9(12):3425-3442. doi:10.7150/thno.33178
    CrossRef - PubMed
18. Zhuang L, Tian J, Zhang X, Wang H, Huang C. Lnc-DC regulates cellular turnover and the HBV-induced immune response by TLR9/STAT3 signaling in dendritic cells. Cell Mol Biol Lett. 2018;23:43. doi:10.1186/s11658-018-0108-y
    CrossRef - PubMed
19. Sokol CL, Camire RB, Jones MC, Luster AD. The chemokine receptor CCR8 promotes the migration of dendritic cells into the lymph node parenchyma to initiate the allergic immune response. Immunity. 2018;49(3):449-463.e6. doi:10.1016/j.immuni.2018.07.012
    CrossRef - PubMed
20. Siddiqui WA, Ahad A, Ahsan H. The mystery of BCL2 family: Bcl-2 proteins and apoptosis: an update. Arch Toxicol. 2015;89(3):289-317. doi:10.1007/s00204-014-1448-7
    CrossRef - PubMed
21. Tessoulin B, Papin A, Gomez-Bougie P, et al. BCL2-family dysregulation in B-cell malignancies: from gene expression regulation to a targeted therapy biomarker. Front Oncol. 2019;8:645. doi:10.3389/fonc.2018.00645
    CrossRef - PubMed
22. Xu HD, Qin ZH. Beclin 1, Bcl-2 and autophagy. Adv Exp Med Biol. 2019;1206:109-126. doi:10.1007/978-981-15-0602-4_5
    CrossRef - PubMed