Patient characteristics
Two deceased patients and one recovered patient with EBV-HLH were enrolled in this study to investigate what deteriorates EBV-HLH after remission. These three patients included one male and two females with a median age of 22 years (range, 16–26 years; Table 2), and showed typical HLH symptoms with EBV infection. Three timepoints were used in this study to represent different disease statuses to determine the factors that may facilitate the progression of EBV-HLH. Specifically, timepoint 1 (T1) for admission when three patients were in a critical condition as shown by laboratory tests and clinical examination (Fig. 1). Timepoint 2 (T2) was remission timepoint when the patients were extensively treated with DEP recipes, and all pothological tests showed that the diseases had remised (Fig. 1). Finally, timepoint 3 (T3) was deterioration phase for patients 1 (P1) and 2 (P2) after relapse with a higher body temperature; lower levels of leukocytes, hemoglobin, and platelet count (Fig. 1B); and sharply increased levels of HLH markers, including ferritin and sCD25 (Fig. 1C, D), and it was at the fully recovery phase for patient 3 (P3) with all clinical signs at a normal range.
Table 2
Clinical and laboratory diagnosis for HLH at admission
Case
|
Sex/
Age,y
|
FEV
|
SPM
|
HPC
|
WBC,
109/L
|
Hb,
g/L
|
PLT,
109/L
|
Ferritin,
ng/ml
|
sCD25,
U/ml
|
Plasma EBV-DNA,
Copies/ml
|
Genetic
defect
|
1
|
F/26
|
+
|
+
|
+
|
0.55
|
54
|
12
|
2174
|
6865
|
1.73E + 04
|
ND
|
2
|
M/25
|
+
|
+
|
+
|
0.77
|
62
|
18
|
45159
|
162045
|
1.53E + 04
|
ND
|
3
|
F/16
|
+
|
+
|
+
|
3.28
|
82
|
213
|
> 8110
|
NT
|
2.28E + 04
|
ND
|
F female, M male, FEV Fever, SPM Splenomegaly, HPC Hemophagocytosis, WBC white blood cell, Hb hemoglobin, PLT platelets, NT not tested, ND not detected. |
The plasma viral load detected using EBV-DNA PCR greatly differed between deceased and recovered patients. P3 had an undetectable EBV level at T2 and T3. However, for fatal cases, viral loads remained at high (T1-T2) and increased to 1 × 10
6.67 and 1 × 10
6.63 copies/mL at T3 for P1 and P2, respectively (Fig.
1E). Importantly, only B cells were infected by EBV in P3, whereas EBV was detected in B, CD8 + T, and NK cells (CD56+) for P1 and NK cells for P2 (Fig.
1F).
NK dysfunction, lower EBV-specific T cell levels, and hypercytokinemia were not observed at the deterioration timepoint
To investigate whether NK dysfunction deteriorates the progress of P1 and P2 from T2 to T3, an NK functionality assay based on the number of CD107a + NK cells per million PBMCs was performed. All patients were found to have a lower level (< 1,000 CD107a + NK cells per million PBMCs) of degranulation against K562 target cells at T1 (Fig. 2A, B). At T2, the ability of NK cells to degranulate target K562 cells increased for the three patients (3,070 CD107a + NK cells for P1, 1,960 CD107a + NK cells for P2, and 2,725 CD107a + NK cells for P3). Surprisingly, NK degranulation was found to sharply increase to 5,250 and 73,905 CD107a + NK cells for P1 and P2, respectively, at T3, which was higher than that for P3 (1,510 CD107a + NK cells; Fig. 2A, B). These results were also supported by the high level of NK cytotoxicity in P1 and P2 at T3 (Additional file 1: Fig. S1).
The role of EBV-specific T cell responses in EBV-HLH progression was further investigated. We showed that P1 and P2 had high EBV-specific CD8 + T cell responses at T1 with 1.43% and 4.83% of IFN-γ + CD8 + T cells, respectively, which were higher than that for P3 (0.37%). The CD8 + T cell response slightly decreased at T2 and then increased at T3 to 0.63% and 6.25% for P1 and P2, respectively, (Fig. 2C, D). In contrast, P3 showed a lower CD8 + T cell response (0.25%) at T3 (Fig. 2D). Meanwhile, Fig. 2D shows that two deceased patients had higher CD4 + T cell responses at T3 than that for recovered patient.
The mortality of HLH was associated with a cytokine storm, including the overproduction of IFN-γ, IL-2, IL-6, IL-12, IL-18, and TNF-α.[17] As expected, P2 had increased levels of IL-6, IFN-γ, IL-2, IL-8, and MIP-1a at T3. IL-4, IL-12, and TNF-α were undetectable for P2 at T3 (Fig. 2E). However, P1 had decreased IL-6, IL-8, and IFN-γ at T3. Other cytokines, including IL-2, IL-4, IL-12, MIP-1a, and TNF-α, for P1 remained at low levels during disease progression (Fig. 2E). The cytokines for P3 were all at low levels at T3, except for IL-8 (5.16 pg/mL; Fig. 2E).
Taken together, the fatal cases were found to show higher levels of NK cell degranulation ability and EBV-specific T cell response at T3 than the recovery case. Meanwhile, cytokine storms were not observed in fatal cases at T3. These findings indicate that neither NK and T cell response nor cytokine storms deteriorate HLH and that other factors promote HLH deterioration.
Transcriptome analysis revealed that NK and NKT subsets increased in percentage and functionality at the HLH deterioration timepoint
To discover which viral or host factors deteriorate HLH progression, scRNA-seq for PBMCs of all three patients using nine samples was performed. Thirteen clusters were defined (Fig. 3A). Following the marker gene expression pattern in each cell cluster, four clusters presenting a high expression of the NK cell markers CD56, GNLY, KLRD1, and KLRC1, were defined. Among which, two clusters also simultaneously expressed T cell markers (i.e., CD3D and CD3E; Fig. 3B). Therefore, these four clusters were designated as NK-3, NK-7, NKT-1, and NKT-11 (Fig. 3C). Notably, the portion of each cluster within the four subsets (i.e., NK-3, NK-7, NKT-1, and NKT-11) differed greatly among the different timepoints (Fig. 3D). The results showed that the proportions of NK-3, NK-7, NKT-1, and NKT-11 cells from P1 were increased from 8%, 25%, 11%, and 13% at T2 to 71%, 53%, 31%, and 74% at T3, respectively. For P2, the percentages of NK-3, NKT-1, and NKT-11 peaked at T3 with 91%, 73%, and 83%, respectively. Meanwhile, P3 showed the highest number of NK and NKT cells at T1 then continue reduced at T3. To characterize the functionality of these four subsets (i.e., NK-3, NK-7, NKT-1, and NKT-11), functional gene expression patterns were compared, and it showed that NK-7 and NK-3 were highly featured by cytotoxic and oxidative phosphorylation signature, respectively (Fig. 3E), NKT-1 showed strong activation and a signature marked by the enrichment of Jun/Fos signaling, and NKT-11 displayed a dual signature marked by the enrichment of proliferation and glycolysis genes (Fig. 3E). Similarly, the expression of Prf1, GZMA, and GZMB, was highly presented in NK and NKT populations, indicating that they possessed a killing capacity. The activation marker CD69 was predominantly observed in NK-7 and NKT-1, whereas the transcripts of IFN-γ were mainly observed in NKT-1 (Fig. 3F). These results suggest that NK and NKT cells are activated. Moreover, the expression of the checkpoint inhibitory receptors PD-1, TIGIT, and CTLA4 were not obvious in NK and NKT cells. Furthermore, NK-7 cells highly expressed Klrb1c (NK1.1), and NKT-1 cells highly expressed Klrg1. All NK and NKT cells downregulated the expression of Itgam (CD11b), Ncr1 (NKP46), Itga2 (CD49b), CD27, and Kit (Fig. 3F).
The percentage of NK and NKT cells with lytic and latent EBV infection substantially increased at the HLH deterioration timepoint
Our scRNA-seq data showed that EBV-infected NKT-1, NKT-11, and NK-3 subsets were significantly different among the three subjects (Fig. 4A). EBV RNA was not detected in all PBMC subsets at T3 for P3; however, high percentages of EBV RNA-positive NKT-1, NKT-11, and NK-3 were detected at T3 for P1 and P2 (Fig. 4A). The infection in the NK and NKT clusters for P1 was persistent within the disease progression, which was 37%, 31% and 67% of NKT-1, NK-3 and NKT-11, respectively, at T1 and 37%, 39% and 42% of NKT-1, NK-3 and NKT-11, respectively, at T3 (Fig. 4B, left panel). Additionally, the EBV infection of NK-3, NKT-1, and NKT-11 for P2 was at low levels (< 10%) at T1 and T2, which sharply increased to 35%, 51%, and 62%, respectively, at T3. Notably, P2 showed a low percentage of EBV-infected NK-7 cells (Fig. 4B middle panel). No EBV RNA was observed for NK and NKT cells at all three timepoints for P3 (Fig. 4B, right panel).
Furthermore, BLLF1, BALF3, BALF5, LF3, BARF1, EBER, EBNA-1, LMP-1, LMP-2A, and RPMS1 were found to be the most frequently detected genes in the deterioration phase in P1 and P2 (Fig. 4C), which resembled a canonical type II latency profile and the lytic cascade. Interestingly, no obvious difference was found between EBV-infected and noninfected NK/NKT cells in terms of the function and expression of cytokines (Additional file 1: Fig. S2), indicating that EBV infection did not influence the function of NK or NKT cells.
To confirm the EBV cell tropism observed by scRNA-seq, a multicolor flow cytometry-based assay (flowRNA) was established to simultaneously detect the abundantly expressed viral noncoding RNAs (EBER-1/2) present in every infected cell for all patients at T3. The results showed that EBV-infected 84.3% of CD3-CD56 + NK cells, 4.19% of CD3 + CD4-T cells, and 0.69% of CD3 + CD56 + NKT cells for P1 at T3 (Fig. 4D). P2 had the highest infection in CD3 + CD56 + NKT cells (67.9%), and 12.1% of CD3-CD56 + NK cells were EBER-positive. No EBER-positive cells were observed in P3 (Fig. 4D). These results are consistent with the results of the scRNA-seq analysis.
EBV-infected cells presented significant enrichment in canonical cancer pathways
Although functionality loss among EBV-infected NK or NKT cells was not observed, the consequences of the infected NK and NKT cells were speculated given that EBV can transform B cells into lymphoma. Therefore, the transcriptional profiles of EBV + NK and NKT subsets were investigated. The results showed that highly infected NKT-1, NK-3, and NKT-11 displayed quite high copy number variations (CNVs). At T3, the percentage of aneuploid cells for NKT-1, NK-3, and NKT-11 was 90%, 23%, and 40%, respectively, for P1. For P2, the percentage of aneuploid cells for NKT-1, NK-3, and NKT-11 was 91%, 40%, and 60% at T3, respectively (Fig. 5A).
Furthermore, the correlation between EBV infection and CNVs was analyzed, and the data showed that 96% of EBV-infected NK-1 had CNVs, which was 46% and 64% for NK-3 and NKT-11, respectively (Fig. 5B), indicating that EBV infection promoted the tumorigenesis of infected NK and NKT cells. The gene enrichment in 10 canonical cancer pathways was compared to confirm the tumorigenesis effect of EBV infection, and the results showed that in P1, except for the Nrf2 and Wnt pathways, EBV-infected cells exhibited significantly higher enrichment in the other eight cancer pathways, including RTK/RAS, PI3K, P53, cell cycle, TGFβ, Hippo, Notch, and Myc pathways, than noninfected cells. All 10 canonical cancer pathways were significantly upregulated in EBV-infected cells in P2 (Fig. 5C). The significant upregulation of the canonical cancer pathways was observed for infected NK and NKT cells (Additional file 1: Fig. S3A).
These activated cells may proliferate as tumor cells because the CNV increased in infected NK and NKT subsets. By comparing differentially regulated genes between EBV-infected and non-EBV-infected cells, genes associated with proto-oncogenes transcription factor (Myc), proliferation (MKI67), and EBV LMP1-related carcinogenesis (TRAF2 and Jak3) were observed to be highly expressed in EBV-positive cells. Conversely, EBV LMP1-related (TRAAD) and LMP2A-related (Lyn) carcinogenesis and anti-apoptosis (Bcl2) genes were downregulated in EBV-positive cells (Fig. 5D). The same results in gene expression could be observed at the disease progression level (Additional file 1: Fig. S3B).